Evaluation of a Natural Language Processing Approach to Identify Social Determinants of Health in Electronic Health Records in a Diverse Community Cohort.

Journal: Medical care

Published Date: Mar 1, 2022

Abstract

BACKGROUND: Health care systems in the United States are increasingly interested in measuring and addressing social determinants of health (SDoH). Advances in electronic health record systems and Natural Language Processing (NLP) create a unique opportunity to systematically document patient SDoH from digitized free-text provider notes.

Authors

Christopher J Rouillard

University of Illinois at Urbana-Champaign Carle Illinois College of Medicine, Champaign, IL.
Mahmoud A Nasser

Mid-Atlantic Permanente Medical Group PC, Kaiser Permanente Mid-Atlantic States, Rockville, MD.
Haihong Hu

Mid-Atlantic Permanente Medical Group PC, Kaiser Permanente Mid-Atlantic States, Rockville, MD.
Douglas W Roblin

Mid-Atlantic Permanente Medical Group PC, Kaiser Permanente Mid-Atlantic States, Rockville, MD.

Keywords

Adolescent Adult Aged Algorithms Cohort Studies Delivery of Health Care District of Columbia Electronic Health Records Female Housing Humans Machine Learning Male Maryland Middle Aged Natural Language Processing Sensitivity and Specificity Social Determinants of Health Surveys and Questionnaires United States Young Adult

External Resources

View on PubMed Access via DOI PubMed (34984989)

Evaluation of a Natural Language Processing Approach to Identify Social Determinants of Health in Electronic Health Records in a Diverse Community Cohort.

Abstract

Authors

Keywords

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